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Microsoft AI-900 certification exam covers a wide range of topics related to AI, including machine learning, natural language processing, computer vision, and conversational AI. It tests one's ability to understand the basic principles of AI and how to apply them to solve real-world problems using the Microsoft Azure platform. Additionally, it evaluates one's knowledge of the ethical and responsible use of AI technologies.
Microsoft AI-900 certification exam is ideal for individuals who work with Azure cloud services or plan to migrate their applications to the Azure cloud. AI-900J exam is also suitable for IT professionals, developers, data analysts, and business analysts who want to gain a basic understanding of AI and its applications in the cloud environment. The AI-900 certification is a valuable addition to the resume of anyone interested in AI and machine learning.
Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900
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About Exam AI-900
The interested candidate for the Microsoft AI-900 test, which also goes under the name the Azure test for AI Fundamentals, should have at least some foundational understanding of the concept of AI features alongside ML ones. This exam will test the entrant's knowledge of different AI common workloads, principles of AI and ML, NLP workloads, and other related concepts. When it comes to the details for this exam, the Microsoft AI-900 is available in several languages, among which you'll find Spanish, English, Korean, German, Chinese (Simplified), and French. Such an exam comes with a registration fee of $99 and should be scheduled through Pearson VUE. Also, in the main exam, candidates will be exposed to around 40-60 tasks with 1 hour given to solve them.
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Microsoft AI-900日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Features of computer vision workloads on Azure | 15-20% | - Computer vision solutions
|
| Fundamentals of machine learning on Azure | 25-30% | - Core machine learning concepts
|
| Describe AI workloads and considerations | 20-25% | - Fundamentals of artificial intelligence concepts
|
| Features of natural language processing (NLP) workloads on Azure | 30-35% | - Text analytics and language understanding
|





